Journal of Geophysical Research: Biogeosciences最新文献

{"title":"Constraining Wetland and Landfill Methane Emission Signatures Through Atmospheric Methane Clumped Isotopologue Measurements","authors":"Jiayang Sun,&nbsp;Cédric Magen,&nbsp;Mojhgan A. Haghnegahdar,&nbsp;Jiarui Liu,&nbsp;Julianne M. Fernandez,&nbsp;James Farquhar","doi":"10.1029/2024JG008249","DOIUrl":"https://doi.org/10.1029/2024JG008249","url":null,"abstract":"<p>Microbial methane emissions are associated with a wide range of isotopic signatures, providing information about the sources and sinks of methane. Methods of directly sampling methane from environments such as wetlands may fail to capture the temporal and spatial variations in emissions at a specific site and time. The Keeling plot method is commonly used to infer the overarching isotopic signatures of methane sources. In this study, we have expanded the application of the Keeling plot from conventional stable isotope ratios to include novel clumped isotopologue compositions of methane. This advancement aims to provide more robust constraints on regional methane emission signatures. We analyzed methane isotopologue compositions from air samples collected above wetlands and landfills across Maryland, USA, and determined the end-member compositions for background air, wetland, and landfill sources. Our findings indicate that the isotopologue compositions of methane from regional wetland emissions exhibit seasonal variations—δ¹³C and δD values become less positive as winter approaches, reflecting changes in methane oxidation and production rates. The continuous monitoring of air methane isotopologue signatures will deepen our understanding of the seasonal patterns in methane emissions and contribute to refining the global methane budget, as valuable insights can be extracted from these measurements.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JG008249","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping Peatland Distribution and Quantifying Peatland Below-Ground Carbon Stocks in Colombia's Eastern Lowlands","authors":"A. Uhde,&nbsp;A. M. Hoyt,&nbsp;L. Hess,&nbsp;C. Schmullius,&nbsp;E. Mendoza,&nbsp;J. C. Benavides,&nbsp;S. Trumbore,&nbsp;J. M. Martín-López,&nbsp;P. N. Skillings-Neira,&nbsp;R. S. Winton","doi":"10.1029/2024JG008505","DOIUrl":"https://doi.org/10.1029/2024JG008505","url":null,"abstract":"<p>The extent and distribution of tropical peatlands, and their importance as a vulnerable carbon (C) store, remain poorly quantified. Although large peatland complexes in Peru, the Congo basin, and Southeast Asia have been mapped in detail, information on many other tropical areas is uncertain. In the Eastern Colombian lowlands, peatland area estimates range from 700 km² to nearly 60,000 km², leading to highly uncertain C stocks. Using new field data, high-resolution Earth observation (EO), and a random forest approach, we mapped peatlands across Colombian territory East of the Andes below 400 m elevation. We estimated peatland extent using two approaches: a conservative method focused on medium-to-high peat probability areas and a more inclusive one accounting for large low-probability areas. Multiplying these extents by below-ground carbon density yields a conservative estimate of 0.95 (0.6–1.39 Pg C, 95% confidence interval) over 9,391 km² (7,369–11,549 km²) and up to 2.86 Pg C (1.76–4.22 Pg C) across 29,069 km² (22,429–36,238 km²). Among four potentially peat-forming ecosystems identified, palm swamps and floodplain forests contributed most to the peat extent and C stock. We found that most peatland patches were relatively small, covering less than 100 ha. We compared our map to previously published global and pan-tropical peat maps and found low spatial overlap among them, suggesting that peat maps uninformed by local field information may not precisely specify which landscape areas within a peatland-rich region are actually peatlands. We further assessed the suitability of different EO and climate variables, highlighting the need for high-resolution data to capture local heterogeneities in the landscape.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JG008505","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143831100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-Native Earthworms Alter Carbon Sequestration in Arctic Tundra Ecosystems","authors":"H. Jonsson,&nbsp;G. Blume-Werry,&nbsp;A. A. Wackett,&nbsp;J. Olofsson,&nbsp;E. Arvidsson,&nbsp;T. Sparrman,&nbsp;J. Klaminder","doi":"10.1029/2024JG008598","DOIUrl":"https://doi.org/10.1029/2024JG008598","url":null,"abstract":"<p>Earthworms, as detritivores, play a significant role in breaking down soil organic carbon (SOC). The introduction of non-native earthworms to arctic ecosystems has, therefore, raised concerns about the potential impact they may have on one of the world's largest SOC reservoirs. Earthworms could also have considerable effects on plant productivity, and the lack of experimental studies quantifying their impact on carbon (C) reservoirs in both soil and plants makes it difficult to predict the effect of earthworms on ecosystem C storage. Here we experimentally tested how earthworms known to be non-native to arctic ecosystems (Aporrectodea spp. and Lumbricus spp.) affect C reservoirs in soil and plants (above and belowground separately) in two common tundra vegetation types (heath and meadow). Earthworms lowered the mean SOC pool and substantially altered SOC quality in meadow soils by increasing the proportion of aromatic-C compounds. Simultaneously, earthworms increased the C pool stored in plant biomass, which counteracted earthworm-induced SOC losses in meadow ecosystems. A positive earthworm effect on belowground biomass in heath soil facilitated a net ecosystem uptake of ∼0.84 kg C m⁻² over the 4-year study period. The higher C uptake into plant biomass in the heath resulted in a notable increase of SOC but lower δ¹³C values, likely because of recently captured C being sourced from roots or litter. Our observations of vegetation-specific feedbacks between plants, earthworms, and soils advance our understanding of non-native earthworms' impact on SOC dynamics and C budgets in high-latitude ecosystems.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JG008598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143831306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability","authors":"Ian Shirley,&nbsp;Sebastian Uhlemann,&nbsp;John Peterson,&nbsp;Katrina Bennett,&nbsp;Susan S. Hubbard,&nbsp;Baptiste Dafflon","doi":"10.1029/2024JG008604","DOIUrl":"https://doi.org/10.1029/2024JG008604","url":null,"abstract":"<p>Snow plays a critical role in carbon cycling, vegetation dynamics, and permafrost hydrology at high latitudes by influencing surface energy exchange. Predicting snow distribution patterns is essential for understanding the evolution of Arctic ecosystems, yet scaling process-level knowledge to landscape predictions remains challenging. Here, we analyze snow depth (2019 and 2022), terrain elevation, and vegetation height from a watershed on the Seward Peninsula, Alaska, to examine how topography and shrubs shape snow redistribution across spatial scales. We find that snow depth is strongly coupled to terrain at scales below ∼60 m but becomes increasingly decoupled at larger scales. The topographic model of snow depth variation, which transforms terrain data to align with these scale-dependent snow patterns, is well correlated with local snow depth variations (linear fit <i>R</i>² &gt; 0.5 for 85% of 100-m patches). A machine learning reconstruction of shrub canopy snow trapping reveals a simple exponential relationship between canopy structure and snow accumulation (<i>R</i>² = 0.59), highlighting the combined influence of topography and vegetation on snow distribution. Together, these empirical relationships capture much of the observed snow variability in the watershed (<i>R</i>² = 0.49, root mean square error (RMSE) = 30 cm), though systematic limitations persist in areas of strong scour and at coarser scales where wind-terrain interactions are more complex. These findings provide a framework for more efficient snow depth prediction and offer insights to improve snow-vegetation feedback representation in Earth System Models.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JG008604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143824631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal Characteristics of Drought Events in Africa's Great Green Wall Region During 1950–2022","authors":"Kidane Welde Reda,&nbsp;Wang Yongdong,&nbsp;You Yuan,&nbsp;Zhou Na,&nbsp;Zinabu Bora,&nbsp;Gebremedhin Gebremeskel Haile,&nbsp;Yikunoamlak Gebrewahid","doi":"10.1029/2024JG008313","DOIUrl":"https://doi.org/10.1029/2024JG008313","url":null,"abstract":"<p>Understanding historical spatiotemporal drought patterns is crucial for effective drought adaptation and mitigation strategies. Despite the launch of Africa's Great Green Wall (AGGW) initiative by the African Union to combat desertification in the semi-arid Sahel region, there remains a limited comprehensive long-term spatiotemporal assessment of drought patterns. In this study, we analyzed the drought spatiotemporal characteristics in the AGGW region using the Standardized Precipitation-Evapotranspiration Index (SPEI) at multiple timescales (1-month, 3-month, 6-month, 9-month, and 12-month) from 1950 to 2022. Despite regional variations, the results showed an overall increasing drought trend across the AGGW during the past 73 years. Trends of drought change per year were −0.012, −0.015, −0.018, −0.009, and −0.021 for SPEI01, SPEI03, SPEI06, SPEI09, and SPEI12, respectively. Significant spatial variability in drought duration, frequency, intensity, and trend were observed, mainly larger values concentrated in the northern and central areas of AGGW. Two significant turning points were detected, occurring in 1973 and 1996 that indicated the periods of 1950–1972 and 1973–1995 non-significant drought increase while significant severe drought occurred in the late periods (1996–2022), with widespread spatial coverage. Seasonal drought variation demonstrates an increasing trend in autumn, spring, summer, and winter across all SPEI time scales, with notably larger rates during autumn and winter. Finally, these findings provide important insights into the characteristics and mechanisms of droughts across the AGGW region and have a significant implication for drought adaptation and mitigation strategies to meet the core objectives of the AGGW regional initiative.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143822173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Coupled O2-CO2 Model for Joint Estimation of Stream Metabolism, O-C Stoichiometry, and Inorganic Carbon Fluxes","authors":"Jacob S. Diamond,&nbsp;E. Bertuzzo","doi":"10.1029/2024JG008401","DOIUrl":"https://doi.org/10.1029/2024JG008401","url":null,"abstract":"&lt;p&gt;We determine where stream carbon dioxide (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) comes from by developing a model for the joint estimation of stream metabolism, oxygen-carbon (O-C) stoichiometry, and fluxes of dissolved inorganic carbon (DIC), based on observations of stream oxygen (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${mathrm{O}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; concentrations. The model is based on a stream reach mass balance of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${mathrm{O}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, DIC, and total alkalinity, and it accounts for the carbonate system and the contribution of lateral flow. &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${mathrm{O}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mtext&gt;DIC&lt;/mtext&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $text{DIC}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; mass balances are coupled through stoichiometric coefficients for photosynthesis and combined autotrophic and heterotrophic respiration. Under the assumption of constant alkalinity and circumneutral pH, the model simplifies and includes 8 parameters, which are estimated through a Bayesian hierarchical framework. The model accurately reproduced time series of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${mathrm{O}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 ","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JG008401","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patterns and Potential Consequences of a Changing Sulfur Cycle in High Elevation Wetlands","authors":"Laura T. Rea,&nbsp;Molly E. Huber,&nbsp;Hannah R. Miller,&nbsp;Clifford Adamchak,&nbsp;Eve-Lyn S. Hinckley","doi":"10.1029/2024JG008616","DOIUrl":"https://doi.org/10.1029/2024JG008616","url":null,"abstract":"<p>Ice thaw and enhanced bedrock weathering are increasing sulfate export in alpine streams, which may change sulfur (S) and other biogeochemical cycles in adjacent wetlands. We compared S and carbon (C) concentrations and sulfate reduction rates (SRRs) across three wetland types in the Colorado Rocky Mountains, USA: snowmelt-fed wetlands (SFWs), periglacial solifluction lobes (PSLs), and subalpine wetlands (SAWs). We found that each wetland type had unique biogeochemical characteristics. Subalpine wetlands had the highest soil C (37.2 ± 8.7%C) and SRRs (29.3 ± 21 nmol mL⁻¹ soil day ⁻¹) compared with SFWs and PSLs, which had lower %C and moderate to low SRRs, respectively. Subalpine wetlands accumulated little sulfate, whereas PSLs had high concentrations (0.04 ± 0.04 vs. 0.6 ± 1.4 mg S g⁻¹ dry soil respectively); SFWs had low sulfate concentrations (0.02 ± 0.01 mg S g⁻¹ dry soil). Sulfate-S stable isotope data suggest different sources of S in the SFWs and PSLs: atmospheric and geologic, respectively. The data indicate that high C supports high SRRs in SAWs, whereas SRRs may be C-limited and co-limited by C and S in PSLs and SFWs, respectively. With climate warming, SAWs have the greatest potential to release more C to the atmosphere, SFWs will likely decrease in size and experience changes in plant community composition, and PSLs may be sources of acid rock drainage. These data demonstrate different biogeochemical fates of S and C in three wetland types present across alpine landscapes, and notable consequences for biogeochemical cycling as warming continues.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Widespread Advances in Corn and Soybean Phenology in Response to Future Climate Change Across the United States","authors":"Yanjun Yang,&nbsp;Bo Tao,&nbsp;Alex C. Ruane,&nbsp;Chaopeng Shen,&nbsp;David S. Matteson,&nbsp;Rémi Cousin,&nbsp;Wei Ren","doi":"10.1029/2024JG008266","DOIUrl":"https://doi.org/10.1029/2024JG008266","url":null,"abstract":"<p>Crop phenology regulates seasonal carbon and water fluxes between croplands and the atmosphere and provides essential information for monitoring and predicting crop growth dynamics and productivity. However, under rapid climate change and more frequent extreme events, future changes in crop phenological shifts have not been well investigated and fully considered in earth system modeling and regional climate assessments. Here, we propose an innovative approach combining remote sensing imagery and machine learning (ML) with climate and survey data to predict future crop phenological shifts across the US corn and soybean systems. Specifically, our projected findings demonstrate distinct acceleration patterns—under the RCP 4.5/RCP 8.5 scenarios, corn planting, silking, maturity, and harvesting stages would significantly advance by 0.94/1.66, 1.13/2.45, 0.89/2.68, and 1.04/2.16 days/decade during 2021–2099, respectively. Soybeans exhibit more muted responses with phenological stages showing relatively smaller negative trends (0.59, 1.08, 0.07, and 0.64 days/decade under the RCP 4.5 vs. 1.24, 1.53, 0.92, and 1.04 days/decade under the RCP 8.5). These spatially explicit projections illustrate how crop phenology would respond to future climate change, highlighting widespread and progressively earlier phenological timing. Based on these findings, we call for a specific effort to quantify the cascading effects of future phenology shifts on crop yield and carbon, water, and energy balances and, accordingly, craft targeted adaptive strategies.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143770184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nitrate-Driven Eutrophication Supports High Nitrous Oxide Production and Emission in Coastal Lagoons","authors":"Henry L. S. Cheung,&nbsp;Mindaugas Zilius,&nbsp;Tobia Politi,&nbsp;Elise Lorre,&nbsp;Irma Vybernaite-Lubiene,&nbsp;Isaac R. Santos,&nbsp;Stefano Bonaglia","doi":"10.1029/2024JG008510","DOIUrl":"https://doi.org/10.1029/2024JG008510","url":null,"abstract":"<p>Under current circumstances, coastal lagoons are net emitters of nitrous oxide (N₂O) to the atmosphere. We hypothesize that widespread nitrogen-driven coastal eutrophication will enhance N₂O production and emissions from coastal lagoons. Here, we quantified spatial and temporal patterns of sediment-water and water-air N₂O fluxes in three large eutrophic lagoons in Europe. Annual sediment N₂O fluxes ranged between −0.3 ± 0.3 (summer) and 10.6 ± 2.0 μmol m⁻² d⁻¹ (spring). In spring, conspicuous sediment effluxes were mainly supported by high nitrate concentrations (89–202 μM) and incomplete denitrification. In summer, a small sediment influx was related to nitrate limitation (0–9 μM), potentially leading to N₂O demand for denitrification. The water-air N₂O fluxes were comparable with benthic fluxes, indicating that sediment was the main source of N₂O to the atmosphere. The hypereutrophic Curonian Lagoon had the largest N₂O emission at 4.9 ± 2.1 μmol m⁻² d⁻¹, while the less eutrophic Oder and Vistula lagoons emitted 2.5 ± 1.0 and 2.0 ± 0.7 μmol m⁻² d⁻¹, respectively. Our observations, combined with earlier measurements in coastal lagoons worldwide, revealed a lagoon median (Q1–Q3) N₂O emission of 14.2 (2.7–29.8) Gg yr⁻¹, which is about 48% higher than previous estimates. Eutrophication driven by large nitrogen inputs is thus a significant driver of coastal N₂O emissions globally.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JG008510","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Turfgrass on Urban Carbon Dioxide Fluxes in Indianapolis, Indiana, USA","authors":"Jason P. Horne,&nbsp;Claire Jin,&nbsp;Natasha L. Miles,&nbsp;Scott J. Richardson,&nbsp;Samantha L. Murphy,&nbsp;Kai Wu,&nbsp;Kenneth J. Davis","doi":"10.1029/2024JG008477","DOIUrl":"https://doi.org/10.1029/2024JG008477","url":null,"abstract":"<p>Evaluating the efficacy of climate mitigation measures requires quantifying urban greenhouse gas (GHG) emissions. Both anthropogenic and biogenic GHG fluxes are important in urban systems, and disaggregation is necessary to understand urban GHG fluxes. In urban environments one common source of biogenic carbon dioxide (CO₂) fluxes is turfgrass. We use CO₂ fluxes measured using eddy covariance over a cemetery (less managed) and golf course (more managed) to investigate the contribution of turfgrass lawns to biogenic CO₂ fluxes in Indianapolis, IN. We assess the ability of a simple light-use efficiency model, the Vegetation Photosynthesis and Respiration Model (VPRM), commonly used to create prior fluxes necessary for determining urban carbon dioxide (CO₂) fluxes via inversion modeling, to represent daily and seasonal patterns in turfgrass CO₂ fluxes. Our results show that the existing VPRM Plant Functional Types (PFTs) cannot capture observed daily and seasonal fluxes at either location. We then use data from these sites to create a new turfgrass PFT for the VPRM. We find that less-managed lawns like cemeteries are best represented by different parameters than heavily managed lawns like golf courses, and seasonally changing parameters best match the observed fluxes. We then use the new turfgrass PFT within the VPRM to explore daily and seasonal variability in turfgrass fluxes and their impact, integrated across the city, on urban ecosystem CO₂ fluxes. This study illustrates the importance of representing turfgrass as a unique PFT when quantifying urban GHG fluxes and the biases resulting from misrepresentation.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}